It is known that an operating efficiency of a gas turbine may be improved by operating a compressor of the turbine at a relatively high pressure ratio. However, if the pressure ratio is allowed to exceed a certain critical value during turbine operation, an undesirable condition known as compressor stall may occur. Compressor stall may reduce the compressor pressure ratio and reduce the airflow delivered to a combustor, thereby adversely affecting the efficiency of the gas turbine. Rotating stall in an axial-type compressor typically occurs at a desired peak performance operating point of the compressor. Following rotating stall, the compressor may transition into a surge condition or a deep stall condition that may result in a loss of efficiency and, if allowed to be prolonged, may lead to catastrophic failure of the gas turbine.
Typically, gas turbines are controlled to provide a desired surge performance margin above a desired peak performance based on a maximum achievable pressure rise across the compressor. One way of controlling a gas turbine to prevent compressor stall is to measure compressor operating parameters such as air flow and pressure rise through the compressor to detect stall “precursors” indicative of a potential stall condition. Signal processing techniques, such as Kalman filtering and Fast Fourier Transform (FFT) processing, have been proposed to detect stall precursors by analyzing signals indicative of compressor operating parameters. If a stall precursor is detected, operation of the gas turbine may be controlled to prevent stall from occurring. However, such control techniques typically rely on prediction of an incipient stall condition, and the prediction of the stall condition may not be provided in a sufficiently long period of time before a stall condition to prevent the stall condition from occurring.